{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:18.638469Z",
     "end_time": "2024-06-08T16:12:18.659224Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 第4章 描述性统计分析与可视化\n",
    "### 变量的度量类型\n",
    "名义：只有名义差别，无高低贵贱区分的。如性别、名族等。可以是字符也可以数字（编码）。无排序概念。\n",
    "等级：只有名义差别，有顺序差别。如学历（小学、中学、大学等）。可以是字符也可以数字。有排序概念。等级变量的差值是没有意义的。\n",
    "连续：如年龄，一定是数值性。连续变量分组可转成等级变量使用。连续变量的差值是有意义的。\n",
    "#### 名义变量的统计量\n",
    "频次=数据集中出现名义变量的数量。\n",
    "$百分比=\\frac{频次}{总数量}$\n",
    "#### 连续变量的统计量\n",
    "##### 集中趋势\n",
    "**均值**：所有数值加总后除以数量。容易被极值带偏。$\\overline{X}=\\frac{\\displaystyle \\sum^{n}_{i = 1}{x_i}}n$\n",
    "**中位数**：按顺序排列的一组数据中居于中间位置的数，代表一个样本、种群或概率分布中的一个数值，其可将数值集合划分为相等的上下两部分。\n",
    "**众数**：指一组数据中出现次数或出现频率最多的数值，它是一种位置平均数，不受极端变量值的影响。众数主要用于测度分类数据的集中趋势，也可以用来测度顺序数据和数值型数据的集中趋势。一组数据可以有多个众数，也可能不存在众数，对于未分组的定量数据，我们一般很少使用众数。\n",
    "有一组数据：$X_1,\\ldots,X_n$，将它按从小到大的顺序排序为：$X_{(1)},\\ldots,X_{(n)}$，则当N为奇数时，$m_{0.5}=X_{(N+1)/2}$；当N为偶数时，$m_{0.5}=\\frac{X_{(N/2)}+X_{(N/2+1)}}2$\n",
    "![众数、中位数和平均数的关系](../image/001.png \"众数、中位数和平均数的关系\")\n",
    "##### 离中趋势\n",
    "**极差**=最大值-最小值\n",
    "**四分位差（IQR）**=上分位数-下分位数\n",
    "**平均绝对偏差（Mean Absolute Deviation)**\n",
    "$MAD=\\frac1n\\displaystyle \\sum^{n}_{i = 1}{|x_i - \\overline{x}|}$\n",
    "**方差(Variance)**\n",
    "$\\sigma^2=\\frac1{n-1}\\displaystyle \\sum^{n}_{i = 1}{(x_i - \\overline{x})^2}$\n",
    "**标准差(Standard Deviation)**\n",
    "$\\sigma=\\sqrt{\\frac1{n-1}\\displaystyle \\sum^{n}_{i = 1}{(x_i - \\overline{x})^2}}$\n",
    "![盒须图](../image/002.png \"盒须图\")\n",
    "##### 偏态和峰态\n",
    "![正态分布](../image/003.png \"正态分布\")\n",
    "![偏度](../image/004.png \"偏度\")\n",
    "集中趋势选择均值还是中位数描述一组数据主要看偏度，右偏选中位数，不偏选均值。"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:18.659224Z",
     "end_time": "2024-06-08T16:12:18.838884Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "       dist  roomnum  halls    AREA   floor  subway  school  price  \\\n0  chaoyang        1      0   46.06  middle       1       0  48850   \n1  chaoyang        1      1   59.09  middle       1       0  46540   \n2   haidian        5      2  278.95    high       1       1  71662   \n3   haidian        3      2  207.00    high       1       1  57972   \n4   fengtai        2      1   53.32     low       1       1  71268   \n\n       all_pr2  \n0   2250031.00  \n1   2750048.60  \n2  19990114.90  \n3  12000204.00  \n4   3800009.76  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>dist</th>\n      <th>roomnum</th>\n      <th>halls</th>\n      <th>AREA</th>\n      <th>floor</th>\n      <th>subway</th>\n      <th>school</th>\n      <th>price</th>\n      <th>all_pr2</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>chaoyang</td>\n      <td>1</td>\n      <td>0</td>\n      <td>46.06</td>\n      <td>middle</td>\n      <td>1</td>\n      <td>0</td>\n      <td>48850</td>\n      <td>2250031.00</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>chaoyang</td>\n      <td>1</td>\n      <td>1</td>\n      <td>59.09</td>\n      <td>middle</td>\n      <td>1</td>\n      <td>0</td>\n      <td>46540</td>\n      <td>2750048.60</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>haidian</td>\n      <td>5</td>\n      <td>2</td>\n      <td>278.95</td>\n      <td>high</td>\n      <td>1</td>\n      <td>1</td>\n      <td>71662</td>\n      <td>19990114.90</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>haidian</td>\n      <td>3</td>\n      <td>2</td>\n      <td>207.00</td>\n      <td>high</td>\n      <td>1</td>\n      <td>1</td>\n      <td>57972</td>\n      <td>12000204.00</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>fengtai</td>\n      <td>2</td>\n      <td>1</td>\n      <td>53.32</td>\n      <td>low</td>\n      <td>1</td>\n      <td>1</td>\n      <td>71268</td>\n      <td>3800009.76</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snd = pd.read_csv('../data/sndHsPr.csv')\n",
    "snd['all_pr2'] = snd[['price', 'AREA']].apply(lambda x: x.iloc[0] * x.iloc[1], axis=1)\n",
    "snd.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "data": {
      "text/plain": "       dist  roomnum  halls    AREA   floor  subway  school  price  \\\n0  chaoyang        1      0   46.06  middle       1       0  48850   \n1  chaoyang        1      1   59.09  middle       1       0  46540   \n2   haidian        5      2  278.95    high       1       1  71662   \n3   haidian        3      2  207.00    high       1       1  57972   \n4   fengtai        2      1   53.32     low       1       1  71268   \n\n       all_pr2 district  \n0   2250031.00      朝阳区  \n1   2750048.60      朝阳区  \n2  19990114.90      海淀区  \n3  12000204.00      海淀区  \n4   3800009.76      丰台区  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>dist</th>\n      <th>roomnum</th>\n      <th>halls</th>\n      <th>AREA</th>\n      <th>floor</th>\n      <th>subway</th>\n      <th>school</th>\n      <th>price</th>\n      <th>all_pr2</th>\n      <th>district</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>chaoyang</td>\n      <td>1</td>\n      <td>0</td>\n      <td>46.06</td>\n      <td>middle</td>\n      <td>1</td>\n      <td>0</td>\n      <td>48850</td>\n      <td>2250031.00</td>\n      <td>朝阳区</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>chaoyang</td>\n      <td>1</td>\n      <td>1</td>\n      <td>59.09</td>\n      <td>middle</td>\n      <td>1</td>\n      <td>0</td>\n      <td>46540</td>\n      <td>2750048.60</td>\n      <td>朝阳区</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>haidian</td>\n      <td>5</td>\n      <td>2</td>\n      <td>278.95</td>\n      <td>high</td>\n      <td>1</td>\n      <td>1</td>\n      <td>71662</td>\n      <td>19990114.90</td>\n      <td>海淀区</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>haidian</td>\n      <td>3</td>\n      <td>2</td>\n      <td>207.00</td>\n      <td>high</td>\n      <td>1</td>\n      <td>1</td>\n      <td>57972</td>\n      <td>12000204.00</td>\n      <td>海淀区</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>fengtai</td>\n      <td>2</td>\n      <td>1</td>\n      <td>53.32</td>\n      <td>low</td>\n      <td>1</td>\n      <td>1</td>\n      <td>71268</td>\n      <td>3800009.76</td>\n      <td>丰台区</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "district = {'fengtai': '丰台区', 'haidian': '海淀区', 'chaoyang': '朝阳区', 'dongcheng': '东城区', 'xicheng': '西城区',\n",
    "            'shijingshan': '石景山区'}\n",
    "snd['district'] = snd.dist.map(district)\n",
    "snd.head()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:18.838884Z",
     "end_time": "2024-06-08T16:12:18.860335Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "data": {
      "text/plain": "district\n丰台区     2947\n海淀区     2919\n朝阳区     2864\n东城区     2783\n西城区     2750\n石景山区    1947\nName: count, dtype: int64"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snd['district'].value_counts()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:18.854683Z",
     "end_time": "2024-06-08T16:12:18.950311Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='district'>"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snd['district'].value_counts().plot(kind='bar')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:18.876130Z",
     "end_time": "2024-06-08T16:12:19.122399Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: ylabel='count'>"
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snd['district'].value_counts().plot(kind='pie')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:19.127821Z",
     "end_time": "2024-06-08T16:12:19.252797Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [
    {
     "data": {
      "text/plain": "61151.810919185686"
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snd['price'].mean()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:19.253293Z",
     "end_time": "2024-06-08T16:12:19.319337Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "57473.0"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snd['price'].median()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:19.280295Z",
     "end_time": "2024-06-08T16:12:19.327349Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "data": {
      "text/plain": "22293.358147328723"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snd['price'].std()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:19.303108Z",
     "end_time": "2024-06-08T16:12:19.327349Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [
    {
     "data": {
      "text/plain": "0.6794935869486859"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snd['price'].skew()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:19.323977Z",
     "end_time": "2024-06-08T16:12:19.389386Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "data": {
      "text/plain": "mean      6.115181e+04\nmedian    5.747300e+04\nsum       9.912709e+08\nstd       2.229336e+04\nskew      6.794936e-01\nName: price, dtype: float64"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snd['price'].agg(['mean', 'median', 'sum', 'std', 'skew'])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:19.343598Z",
     "end_time": "2024-06-08T16:12:19.392710Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "data": {
      "text/plain": "0.01     27104.45\n0.50     57473.00\n0.99    119996.85\nName: price, dtype: float64"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snd['price'].quantile([0.01, 0.5, 0.99])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:19.369239Z",
     "end_time": "2024-06-08T16:12:19.392710Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: >"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snd['price'].hist(bins=30)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:19.392710Z",
     "end_time": "2024-06-08T16:12:19.624690Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [
    {
     "data": {
      "text/plain": "school       0     1\ndistrict            \n东城区       1508  1275\n丰台区       2853    94\n朝阳区       2267   597\n海淀区       1533  1386\n石景山区      1929    18\n西城区       1207  1543",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th>school</th>\n      <th>0</th>\n      <th>1</th>\n    </tr>\n    <tr>\n      <th>district</th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>东城区</th>\n      <td>1508</td>\n      <td>1275</td>\n    </tr>\n    <tr>\n      <th>丰台区</th>\n      <td>2853</td>\n      <td>94</td>\n    </tr>\n    <tr>\n      <th>朝阳区</th>\n      <td>2267</td>\n      <td>597</td>\n    </tr>\n    <tr>\n      <th>海淀区</th>\n      <td>1533</td>\n      <td>1386</td>\n    </tr>\n    <tr>\n      <th>石景山区</th>\n      <td>1929</td>\n      <td>18</td>\n    </tr>\n    <tr>\n      <th>西城区</th>\n      <td>1207</td>\n      <td>1543</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_sch = pd.crosstab(snd['district'], snd['school'])\n",
    "sub_sch"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:19.624690Z",
     "end_time": "2024-06-08T16:12:19.640434Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='district'>"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_sch.plot(kind='bar')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:19.640434Z",
     "end_time": "2024-06-08T16:12:19.842914Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='district'>"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_sch.plot(kind='bar', stacked=True)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:19.846473Z",
     "end_time": "2024-06-08T16:12:20.024057Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [
    {
     "data": {
      "text/plain": "school       0     1  sum1\ndistrict                  \n东城区       1508  1275  2783\n丰台区       2853    94  2947\n朝阳区       2267   597  2864\n海淀区       1533  1386  2919\n石景山区      1929    18  1947",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th>school</th>\n      <th>0</th>\n      <th>1</th>\n      <th>sum1</th>\n    </tr>\n    <tr>\n      <th>district</th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>东城区</th>\n      <td>1508</td>\n      <td>1275</td>\n      <td>2783</td>\n    </tr>\n    <tr>\n      <th>丰台区</th>\n      <td>2853</td>\n      <td>94</td>\n      <td>2947</td>\n    </tr>\n    <tr>\n      <th>朝阳区</th>\n      <td>2267</td>\n      <td>597</td>\n      <td>2864</td>\n    </tr>\n    <tr>\n      <th>海淀区</th>\n      <td>1533</td>\n      <td>1386</td>\n      <td>2919</td>\n    </tr>\n    <tr>\n      <th>石景山区</th>\n      <td>1929</td>\n      <td>18</td>\n      <td>1947</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 标准化堆叠柱形图\n",
    "sub_sch['sum1'] = sub_sch.sum(1)\n",
    "sub_sch.head()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:20.024057Z",
     "end_time": "2024-06-08T16:12:20.061452Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [
    {
     "data": {
      "text/plain": "school           0         1  sum1\ndistrict                          \n东城区       0.541861  0.458139   1.0\n丰台区       0.968103  0.031897   1.0\n朝阳区       0.791550  0.208450   1.0\n海淀区       0.525180  0.474820   1.0\n石景山区      0.990755  0.009245   1.0\n西城区       0.438909  0.561091   1.0",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th>school</th>\n      <th>0</th>\n      <th>1</th>\n      <th>sum1</th>\n    </tr>\n    <tr>\n      <th>district</th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>东城区</th>\n      <td>0.541861</td>\n      <td>0.458139</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>丰台区</th>\n      <td>0.968103</td>\n      <td>0.031897</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>朝阳区</th>\n      <td>0.791550</td>\n      <td>0.208450</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>海淀区</th>\n      <td>0.525180</td>\n      <td>0.474820</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>石景山区</th>\n      <td>0.990755</td>\n      <td>0.009245</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>西城区</th>\n      <td>0.438909</td>\n      <td>0.561091</td>\n      <td>1.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_sch = sub_sch.div(sub_sch['sum1'], axis=0)\n",
    "sub_sch"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:20.039974Z",
     "end_time": "2024-06-08T16:12:20.094363Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='district'>"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_sch = sub_sch.drop('sum1', axis=1)\n",
    "sub_sch.plot(kind='bar', stacked=True)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:20.061950Z",
     "end_time": "2024-06-08T16:12:20.313333Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from stack2dim import *\n",
    "\n",
    "stack2dim(snd, i='district', j='school')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:20.264885Z",
     "end_time": "2024-06-08T16:12:20.478482Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='district'>"
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snd['price'].groupby(snd['district']).mean().plot(kind='bar')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:20.482094Z",
     "end_time": "2024-06-08T16:12:20.643840Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: ylabel='district'>"
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snd['price'].groupby(snd['district']).mean().sort_values(ascending=True).plot(kind='barh')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:20.643840Z",
     "end_time": "2024-06-08T16:12:20.829644Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Python310\\lib\\site-packages\\seaborn\\_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "C:\\Python310\\lib\\site-packages\\seaborn\\_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "C:\\Python310\\lib\\site-packages\\seaborn\\_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Axes: xlabel='district', ylabel='price'>"
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='district', y='price', data=snd)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:20.829644Z",
     "end_time": "2024-06-08T16:12:21.008851Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\58248\\AppData\\Local\\Temp\\ipykernel_2476\\463742255.py:1: FutureWarning: The provided callable <function mean at 0x000001686B686680> is currently using DataFrameGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n",
      "  snd.pivot_table(values='price', index='district', columns='school', aggfunc=np.mean)\n"
     ]
    },
    {
     "data": {
      "text/plain": "school               0             1\ndistrict                            \n东城区       66276.887931  78514.900392\n丰台区       42291.003505  48871.617021\n朝阳区       51588.511689  57403.405360\n海淀区       61385.803653  76911.258297\n石景山区      40353.883878  33107.333333\n西城区       76989.369511  92468.873623",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th>school</th>\n      <th>0</th>\n      <th>1</th>\n    </tr>\n    <tr>\n      <th>district</th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>东城区</th>\n      <td>66276.887931</td>\n      <td>78514.900392</td>\n    </tr>\n    <tr>\n      <th>丰台区</th>\n      <td>42291.003505</td>\n      <td>48871.617021</td>\n    </tr>\n    <tr>\n      <th>朝阳区</th>\n      <td>51588.511689</td>\n      <td>57403.405360</td>\n    </tr>\n    <tr>\n      <th>海淀区</th>\n      <td>61385.803653</td>\n      <td>76911.258297</td>\n    </tr>\n    <tr>\n      <th>石景山区</th>\n      <td>40353.883878</td>\n      <td>33107.333333</td>\n    </tr>\n    <tr>\n      <th>西城区</th>\n      <td>76989.369511</td>\n      <td>92468.873623</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snd.pivot_table(values='price', index='district', columns='school', aggfunc=np.mean)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:21.008851Z",
     "end_time": "2024-06-08T16:12:21.077583Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\58248\\AppData\\Local\\Temp\\ipykernel_2476\\1725508462.py:1: FutureWarning: The provided callable <function mean at 0x000001686B686680> is currently using DataFrameGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n",
      "  snd.pivot_table(values='price', index='district', columns='school', aggfunc=np.mean).plot(kind='bar')\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Axes: xlabel='district'>"
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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T7epb0ldZQIABgJLEVYb4E3ZmZmvzgeOW9FU3POTSMxmEQ0gAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAFIPL7bG0P4fDYWl/AABUFH6+LsAkDrtNT364Xjszsy3p79bocD3drr4lfQEAUJEQYIppZ2a2Nh84bklfdcNDLOkHAICKhkNIAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAgyeX2WNqfw+GwtD8Ahfld7oLjxo3Trl279O9//1uStH37dqWmpmrfvn267777NHToUNlsNknS2rVr9cILLygrK0v9+vVT7969vf0sW7ZMY8aMUX5+voYNG6a77rrL2zZjxgxNnDhRQUFBGjVqlFq1anW55QLARTnsNj354XrtzMy2pL9bo8P1dLv6lvQF4FyXFWC2bdummTNnatGiRZIkp9Opfv36KSEhQa+99ppGjRqltLQ0JScnKysrS/3791fv3r111113adCgQbrhhhvUsmVLbd++XUOGDNELL7ygxo0b629/+5saNGig6667TitXrtSYMWP06quvqkqVKnr66ac1b948Va5c2dIBAIAzdmZma/OB45b0VTc8xJJ+AJxfsQ8hud1u/f3vf9dDDz2kqKgoSdI333yj7OxspaamqlatWho0aJDmzZsnSVq0aJGqVaumAQMGqE6dOkpJSfG2zZ07V/Hx8eratauio6PVo0cPLVy4UJI0a9Ysde7cWW3btlXTpk2VlJSkzz//3Kr1BgAABiv2HphZs2Zp+/btuv/++7VixQrdfPPN2rZtm2JjYxUUFCRJio6O1q5duyRJ6enpio+P9x5Oaty4scaPHy/p9J6cNm3aePtu3LixJk6c6G0bMmRIobZ169apa9euRa7V5XIVd/UuypRj2lavd1l3Zn0r2nqXhIo8lvx+l01sk2aw6vMpTj/FCjA5OTl64403FBUVpQMHDmjhwoWaPHmymjdvrsjISO98NptNdrtdx44dU3Z2turWrettCw0NVWZmpre/s5craltRbdq0qVjzX0xQUJAaNGhgWX8lKT09Xbm5ub4uo9RZ+XlXdBVtLPn9LvvYJss2X2yXxQown332mXJzczVt2jRVqVJFBQUF6tSpk+bPn68uXboUmjcwMFB5eXlyOBwKCAg4Z7qky24rqpiYGKMSrFWio6N9XUKpcrlc2rRpU4X9vK3EWJZ9/H6jLLJquzzzeRdFsQLMwYMHFRsbqypVqpxe2M9P0dHR2r17t7KysgrNm5OTI39/f4WFhRVqOzNd0iXbjh49et62onI4HBVyg6+I6yxV3M+7JDCWZVdF/VzYJss2X3w2xTqJt0aNGjp16lShaQcOHNDw4cO1YcMG77T9+/fL6XQqLCxMMTExhdq2bNmi6tWrS9Il29avX3/eNgAAULEVK8Dccsst2rlzp2bNmqWDBw/qgw8+0LZt23THHXcoOztb8+fPlyS99dZbat26tRwOhxITE/Xjjz/q+++/V35+vqZMmaKEhARJUrt27bR06VKlp6crJydH06dPL9Q2c+ZMHTp0SEeOHNG8efO8bQAAoGIr1iGkypUr6+2339bYsWM1evRohYeH61//+pciIiI0atQoDR48WGPHjpXdbtf06dMlSVWqVFFqaqr69u2r4OBgXXHFFRo9erQkqX79+urVq5eSk5MVGBio2rVrq3v37pKkxMRELVu2THfccYckqVWrVt6fAQBAxVbsy6ibNWum2bNnnzM9KSlJn332mTZv3qzY2NhCN5zr1q2bEhIStHv3bjVv3lwhIf+7wdPAgQPVqVMnHTp0SHFxcd4Td202m8aNG6eePXsqNzdXLVq08F6KDQAAKrbLfpTA+YSHh+vWW289b1tUVJT3xnd/VK9ePdWrV++8bY0bN7aqPAAAUE7wMEcAAGAcAgyAQop7uwIA8AUCDIBCGjW4wfp7Orgr3m3gAZQsS8+BAWA+u5+/NP8R6ch2azq8+i9S8hRr+gKA/48AA+BcR7ZLGRt9XQUAXBCHkAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgxgMJfbY2l/DofD0v4AoKT4+boAAJfPYbfpyQ/Xa2dmtiX93Rodrqfb1bekLwAoSQQYwHA7M7O1+cBxS/qqGx5iST8AUNI4hAQAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDMoFf39/X5cAAChFBBiUC40a3GD9XWTdLmv7AwBYhhvZoVyw+/lL8x+Rjmy3psOr/yIlT7GmLwCA5QgwKD+ObJcyNvq6CgBAKeAQEgAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMPAJl9tjWV8Oh8OyvgAAZvDzdQGomBx2m578cL12Zmb/6b5ujQ7X0+3qW1AVAMAUBBj4zM7MbG0+cPxP91M3PMSCagAAJuEQEgAAMA4BBgAAGOeyA0yfPn2UlpYmSVq7dq3at2+v+Ph4TZ06tdB8y5Yt02233aaEhAQtWbKkUNuMGTPUunVrJSUladWqVYXaXnvtNcXFxalTp07atm3b5ZYJAADKocsKMIsWLdK3334rScrKylL//v3VsWNHzZ49W4sXL9bq1aslSdu3b9eQIUOUkpKid999VxMmTNDu3bslSStXrtSYMWM0YsQIjRs3Ts8995yOHj0qSfrwww/14YcfavLkyXrqqac0aNAgOZ1OK9YXAACUA8UOML///rvGjBmja6+9VtLpMFOtWjUNGDBAderUUUpKiubNmydJmjt3ruLj49W1a1dFR0erR48eWrhwoSRp1qxZ6ty5s9q2baumTZsqKSlJn3/+ubetT58+at68uZKSknTttdfqhx9+sGqdAQAG8ff393UJKIOKfRXSmDFj1LZtW506dUqSlJ6ervj4eNlsNklS48aNNX78eEnStm3b1KZNG++yjRs31sSJE71tQ4YMKdS2bt063Xfffdq+fbtGjhxZqO3nn39W69ati1Wry+Uq7updlCn3G7F6vUsCY2kNU8ZRYiytUtbHUZJks8tht1nSlcPh0A0NGpqx3hYzZZuUrNsui9NPsQLM6tWrtWrVKi1ZskSjRo2SJGVnZ6tu3breeUJDQ5WZmSlJysnJUWRkZLHacnJy5Ha7z2nbs2dPcUqVJG3atKnYy1xIUFCQGjRoYFl/JSk9PV25ubm+LuOCGEtrmDSOEmNplbI8jtL/xtKq+zzVqxaq1x9ooi1byvZ6W82kbVLyzXZZ5ABz6tQpvfDCC3rxxRcVGhrqne5wOBQQEOB9HRgYqLy8vMtu8/M7XdLZbQEBAd7liiMmJsaoBGuV6OhoX5dQbjCW1mEsrWHKOFp1n6czrr/+etntXDhbVlm1XbpcriLvfChygJk0aZIaNWqkW2+9tdD0sLAwZWVleV/n5OR4j1dequ3MSbtnt1WqVEmVKlVSVlaWNyidvVxxOByOChlgKuI6lxTG0jqMpTUq6jja7fYKu+4m8MVnU+QAs3jxYh09elTNmzeXJOXl5emTTz6RJDVp0sQ735YtW1S9enVJp/eAbNiwQV27dj1v2/r169WqVatz2ho1aqT169erVq1akqStW7d6TxoGAAAo8v64mTNnavHixVqwYIEWLFigxMREPfHEE/ryyy/1448/6vvvv1d+fr6mTJmihIQESVK7du20dOlSpaenKycnR9OnTy/UNnPmTB06dEhHjhzRvHnzCrVNmTJF2dnZ2rNnj5YvX+5tAwAAKPIemBo1ahR6HRwcrMqVK6tKlSpKTU1V3759FRwcrCuuuEKjR4+WJNWvX1+9evVScnKyAgMDVbt2bXXv3l2SlJiYqGXLlumOO+6QJLVq1cr78wMPPKAVK1aoTZs2cjqd6tq1qxo1amTJCgMAAPNd9sMcz4QUSerWrZsSEhK0e/duNW/eXCEh/3u43sCBA9WpUycdOnRIcXFx3pNzbTabxo0bp549eyo3N1ctWrTwXoodEBCgqVOn6scff1RAQIAaN258uWUCAIByyLKnUUdFRSkqKuq8bfXq1VO9evXO23ahcGK3273n2wAAAJyNa9IAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAECZFR4aKLldcjgc1nbsdlnbH0qdn68LAADgQq4M8pPsDmn+I9KR7dZ0evVfpOQp1vQFnyHAAADKviPbpYyNvq4CZQiHkAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGCcYgWYzz//XElJSWrQoIHuuece7dq1S5K0fft2JScnKy4uTmPGjJHH4/Eus3btWrVv317x8fGaOnVqof6WLVum2267TQkJCVqyZEmhthkzZqh169ZKSkrSqlWrLnf9AABAOVTkALNv3z4NHz5cgwcP1jfffKM6dero2WefldPpVL9+/dSwYUPNnz9fu3btUlpamiQpKytL/fv3V8eOHTV79mwtXrxYq1evlnQ69AwZMkQpKSl69913NWHCBO3evVuStHLlSo0ZM0YjRozQuHHj9Nxzz+no0aMlsPoAAMBERQ4wu3bt0uDBg9WhQwddffXV6tatm7Zu3apvvvlG2dnZSk1NVa1atTRo0CDNmzdPkrRo0SJVq1ZNAwYMUJ06dZSSkuJtmzt3ruLj49W1a1dFR0erR48eWrhwoSRp1qxZ6ty5s9q2baumTZsqKSlJn3/+eQmsPgAAMJFfUWe87bbbCr3es2ePateurW3btik2NlZBQUGSpOjoaO+hpfT0dMXHx8tms0mSGjdurPHjx0uStm3bpjZt2nj7a9y4sSZOnOhtGzJkSKG2devWqWvXrsVaOZfLVaz5L8XhcFjaX0mxer1LAmNpDVPGUWIsrVLWx1FiLK1iyjhK1o1lcfopcoA5m9Pp1NSpU/XQQw9p3759ioyM9LbZbDbZ7XYdO3ZM2dnZqlu3rrctNDRUmZmZkqScnJxCyxW1rTg2bdpU7GUuJCgoSA0aNLCsv5KUnp6u3NxcX5dxQYylNUwaR4mxtEpZHkeJsbSKSeMo+WYsLyvAvPHGGwoKClLXrl31r3/9SwEBAYXaAwMDlZeXJ4fDUajtzHRJl91WHDExMUYlWKtER0f7uoRyg7G0DmNpDcbROoyldawaS5fLVeSdD8UOMKtWrdKMGTM0Z84c+fv7KywsTDt27Cg0T05OjrctKyvrnOmSLtl29km7Z7cVh8PhqJABpiKuc0lhLK3DWFqDcbQOY2kdX4xlsS6j3r9/vwYPHqy///3vqlevnqTTezk2bNhQaB6n06mwsLBz2rZs2aLq1aufd7k/tq1fv/68bQAAAEUOMHl5eerXr5+SkpJ0++23KycnRzk5OWrevLmys7M1f/58SdJbb72l1q1by+FwKDExUT/++KO+//575efna8qUKUpISJAktWvXTkuXLlV6erpycnI0ffr0Qm0zZ87UoUOHdOTIEc2bN8/bBgAAUORDSN9++6127typnTt3as6cOd7pK1as0KhRozR48GCNHTtWdrtd06dPlyRVqVJFqamp6tu3r4KDg3XFFVdo9OjRkqT69eurV69eSk5OVmBgoGrXrq3u3btLkhITE7Vs2TLdcccdkqRWrVp5fwYAAChygGnbtq3S09PP2xYZGanPPvtMmzdvVmxsrCpXruxt69atmxISErR79241b95cISEh3raBAweqU6dOOnTokOLi4rwn7tpsNo0bN049e/ZUbm6uWrRo4b0UGwAA4LKuQjqf8PBw3Xrrredti4qKUlRU1Hnb6tWr5z2f5o8aN25sVXkAAKAc4WGOAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHHKdIDZvn27kpOTFRcXpzFjxsjj8fi6JAAAUAaU2QDjdDrVr18/NWzYUPPnz9euXbuUlpbm67IAAEAZUGYDzDfffKPs7GylpqaqVq1aGjRokObNm+frsgAAQBng5+sCLmTbtm2KjY1VUFCQJCk6Olq7du0q0rJnDjU5nU45HA7LanI4HLqhRogCLeqyTtUguVwuKbyhZA/88x1WrSe5XKf7LOOsHEvLx1EyZizL/DYpMZb8fv8pbJNleJuULB/LM/0U5ZQRm6eMnlgyevRonTp1Si+88IJ3WsuWLbV8+XKFhYVddFmn06lNmzaVdIkAAKAExMTEKCAg4KLzlNk9MA6H45ziAwMDlZeXd8kA4+fnp5iYGNntdtlstpIsEwAAWMTj8cjtdsvP79LxpMwGmLCwMO3YsaPQtJycHPn7+19yWbvdfsnkBgAAzFVmT+KNiYnRhg0bvK/3798vp9N5yb0vAACg/CuzASYuLk7Z2dmaP3++JOmtt95S69atLT0pFwAAmKnMnsQrSStWrNDgwYMVGBgou92u6dOnq169er4uCwAA+FiZDjCSdPjwYW3evFmxsbGqXLmyr8sBAABlQJkPMAAAAH9UZs+BAQAAuBACDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAwBgzZswo8ry9e/dWQUFBCVZjNsbSOoylNb788ssiz5uamlrmnyTtaxVhuyTAlJKKsDGVtPHjx0uSTp06dU6b0+nUs88+631+1t69e4v0MLCKirG0DmNpjUGDBl2wzePxaNKkSTp8+LAkac2aNdyV/RIqwnZJgCklFWFjKmlnxmTkyJF68803vdNzc3P10EMPac2aNXK73ZLEU8gvgbG0DmNpjTPjOH78eC1YsMA73eVyaeDAgZo2bZp2797to+rMUxG2SwJMKakIG1NpiY2N1bx589SzZ0/t3btXjz/+uI4ePapZs2YpOjra1+UZhbG0DmP555z5dy8wMFAvvfSSnnnmGZ04cULPPfecfvjhB82cOVPx8fGF5sWlleftkgBTysrzxlRaunbtqo8//lg1atRQ+/bttX37dr3//vsKDw/3dWnGYSytw1ha4/HHH9fSpUt14MAB3XrrrVqxYoWmTp2qunXr+ro0I5Xn7ZIAU8rK88ZUmkJCQtSkSROFhobq5MmT2rp1q69LMhZjaR3G0hoRERF68MEH5XQ6ZbPZlJeX5+uSjFZet0sCjA+U142pNK1Zs0bjxo3TpEmTNHHiRKWmpuqLL77wdVlGYiytw1haY9u2bRo+fLjGjRun4cOH67HHHtPGjRt9XZaxyu126UGpiIuL8/68evVqz4033uhZt26dZ9WqVZ6WLVt6VqxY4W1PTEz0RYll3pkx/O233zw333yz54MPPvC2/fe///XEx8d7Nm/e7PF4GMNLYSytw1ha48w4njx50tO+fXvPq6++6m379NNPPTfddJNn3759Ho+HcSyKirBdsgemlGVlZenpp5/WoEGD1Lx5c7Vs2VITJ07U8OHDtWXLFl+XZ4Rdu3apYcOG6tmzp3da06ZN1atXLw0cOFAej0ceHrJeJIyldRhLa6xbt07BwcF64oknvNNuv/12dejQQX/7298Yx2Iqz9sl1+qWskttTMuWLTN2YyotcXFxiouLO2f6I488onr16slms3GVQhExltZhLK3Rpk0btWzZ8pz7vDzxxBNKS0tjDIupPG+XBJhSVp43ppKWn5+vH3744aIBr3Llylq3bt1577eD/2EsrcNYWsPtdisjI+Oi49i2bVsdOHDAe8sJXFhF2C4JMKWkImxMJa1y5cp64YUXZLdf/Min2+1WYGBgKVVlJsbSOoylNbKzs9WhQ4eLzmOz2eR2u+V0OkupKnNVhO3S5uF4RalITExUUFBQkTamvLw8rVixopQqAwDAPAQYACgFp06dMvabLsqvHTt2eE9fMA2HkMoYkzem0nbixAl99NFH6tWrl69LMc7bb7+tvLy8S+4RzM/PV0JCwnnP28L/TJs2TSdPnlRycrJ+//13/eUvfzlnnvT0dA0ZMkSffvqpDyo0R3Z2tv7v//7vgs+Dczqdys/PV7NmzUq5MrO43W4dOHBAL730kt555x3t27dPHo9HtWvX9s6zf/9+9evXTw6HQ9OmTVNERIQPKy4+AkwpqQgbU2k6dOiQHnnkEfn5+enee+/Vjz/+KH9/f9lsNnk8HuXn5+uWW27xdZll1ocffqiOHTueM+2BBx7wvp4/f77uu+++S4YcnA4wXbp0kSR169ZN//3vf1VQUKDRo0frueeekyQFBQXp2LFjvizTCFu3btWjjz4qPz+/836Ry87O1hVXXKG1a9f6oDpz9O/fXxEREVq1apUkacaMGZo5c6Zq1KihVq1aKSkpSa1atdItt9yi7777TldccYWPKy4+AkwpqQgbU2nZu3evHnroIR08eFCffvqpHA6HHnvsMV1zzTXyeDzKyMhQRERE+bjTZAkaPHhwodcff/xxoWlfffWVBg0aVNplGevxxx+XJAUHB0uS7Ha7Pv/8c2+AycnJUeXKlX1Wnyni4uK0YcOGi7YTXi7tzjvvVOfOnfXJJ59IklJTU/XMM89o7969mjt3rp566im53W7FxMRo+vTpCg0N9XHFxUeAKSUVYWMqDTt27FDv3r111113ae3atcrNzfW2nTnxuX79+vr44499VaIRzvfNlsOWl8flchW6utDPz08ZGRlyu93eQO3xePTzzz/rmmuu8WGl5QPb6aUVFBRo7dq12rx5s3JzczVo0CD9/vvvysrK0t69e3X11VfrzjvvVEhIiJYtW6Zjx46pWrVqvi672AgwpaCibEyloVq1anr44Yf18MMPq0+fPjp27JgiIyML/aPGP3AoLcuWLVNqamqhhw2ePHlSffr0kcfjUXBwsB5++GFJ0sGDB70/AyUpPz9f1157rUJCQuTv768OHTooLCxMJ0+e1HXXXacrr7xSfn5+CgkJ0XXXXadHH31UaWlpqlKliq9LLxYCTCmoKBtTaQgLC/P+Ebjqqqu85xSc/Q2YC+suzePxaNSoUYWm/f7774WmZWZmatSoUYqPj9ftt99e2iUaoXHjxpo6dWqhQ20hISFaunRpofkyMzN13333qWvXrqVdohGcTqfWrVvnPY/tYgoKCkqpKnMFBQWpb9++kqQ33nhDbdu2lSQ1bNhQderUUUFBgfLz85WTk6OJEyeqTZs2ys7ONu5vDgGmFFSUjamkvffee0pMTFSdOnUkSVdccYWOHz/u26IM9fDDDys3N7fQ7doHDBhQaJ7HHntMBQUFCgkJKe3yjFGzZk3VrFmz0B9dl8slSfruu+9UUFCgwMBAjR49WsOGDVONGjV8VWqZdvz4cf39739XYGDgOY8Q+CNu9Fk8Z2+bISEhhQ6vjxw5UsuXL9eIESN8UdqfRoApZeV5YypJ+fn5+vTTT/X2229r8uTJatKkiUJCQriq4zJlZmYqKSlJsbGx3mkFBQX66KOPtGnTJjVq1Ej333+/Dys0i8fj0eDBg9W7d29vqP7666+1fPlyHTp0SM2bN1fDhg19XGXZdfXVVxf55p1c0l88ubm5SkpKkvS/ux2HhoYqKipKLVu2VOfOnX1b4J/AjexK2Y033qiqVatKkjIyMlSnTp1zNiZ/f38fV1k2eTweTZ8+XRMmTNArr7yi9PR05eXlKSUlRc2aNdPWrVslSTfccIPWr1+vSpUq+bjisqtZs2YKDw/XiRMn1Lp1a914442aOXOm6tSpo+bNm2vKlCmaNGlSoYCDC1uyZIny8vLUsmVL+fv7q3r16t62X3/9VXPmzNGcOXP06KOPch7Mn9SiRQuuQiqG/fv3KyMjQ2FhYbrqqquUn5+vrKwsLVq0SD/99JOOHDmikSNH6qabbvJ1qcXGHphStnjx4gtuTHPnztXkyZON3ZhKms1mU69evVS/fn09+eSTqlWrliIjIyWdDjcTJ070Phr+3//+t1JSUhQQEODjqsummjVravHixTpw4IC++eYbrVy5Uo899pjuvvtuSdKBAwf0f//3fwSYIsjPz9eSJUv0+OOPKzIyUunp6ZKk6tWra/ny5crOztbAgQPVpUsXPf/88+rVq9cFb9IGWC0qKkqTJ0/WzTffrPbt20uSIiMjNWHCBA0cOFAZGRkaOnSoli9fbtzVr+yB8YHhw4cX2pik00+j7tOnjzIyMjR+/HgjN6bStHHjRvXq1UtRUVFKS0vT4MGDFRAQILvdLrfbLZfLpdGjR7MX5gKSkpL08ssvX/CEZ6fTWSj8tWrVqrRKM05qaqp++uknffDBBwoODlbnzp0VFxenUaNGafHixZowYYJCQkL0zDPPqGXLllwldwn79+/XqlWrLnhC70svvaT169f7oDKztGjRwvs7nJ2drcDAwEJ793NycnTPPffoxRdf1NGjR428RxEBppRUhI2ptC1YsEChoaHek6JRdD179lRAQMAl/5i6XC4VFBRo+vTppVSZWdxut/7xj3+of//+qlq1ql577TV9++23mjVrlvf33eVyaebMmXr11VfVo0cPDRkyxMdVl21r167VP//5TzkcjnO2z4KCAhUUFCgtLc1H1ZkjMzPT+wVu1KhRatWqVaF/K48cOaIuXbroq6++UlhYmK/K/FMIMKWkImxMvpSfn68NGzaoWbNm3PoePnPs2DGdPHlSERERys/PL/QlZcuWLQoKCtK1117rwwpREa1YsUK1atXS9ddfX2j6u+++q3vvvdfYK14JMD5QXjem0uB0OjV79mz17Nmz0PTs7GzFxcVp48aNnPdSBM8884wCAwMvGfYcDodatmzJfWAuoXv37po5c2ahaW3atNHnn3+ugIAAuVwuvfbaa+x9QanJy8tT7969NWvWLF+XUmI4k6yU/fjjj95L2qTT9z+48sorJUkPPfSQhg8frs6dO3POwQXYbDa9+uqr6tmzp44fP66+ffvq3Xff9d6rhPBSNF9//bWeeeYZSdK3336rwMBA7+Wpr7/+up588klJp++58fzzzyspKYk9Wxfx66+/Sjp975zjx48rMDBQx44d0/DhwxUcHCx/f38tWrRItWvXVocOHbi3ThEcPXpUDzzwgJYvX15o+s6dOxUSEsLDbi8hMDBQJ06c8L7u2rXrec8rOvPw27lz55Z2iX8aAaYUeTwe9erVSz///LOk09fnd+jQQd9++63cbreGDBmiH374Qb179/ZxpWWXv7+/AgMDJUmVKlXSxo0bValSJdlstkveAAv/ExwcrHvvvVfS6RAdEhLiff3ee+95f5akffv2KT8/3zvuONeZq4p27NihDz/8UKdOndKDDz6onj176tSpUzp16pSWLFmiL774Qps2beJeT+exf/9+BQQEyO126+TJk6pdu/Z5v5BMmDBBzZo101//+lcfVGkOm81WKKwcOnRI77//vqT/nSh9//33q3///po8ebKPqvxzCDClyGazKSgoyPv67BN5n332WW3cuFEzZ85UVFSUr0o0wplfyjNXHRFcLk9eXp48Ho/3TtD5+fnnvbx36NChPqjOXNWqVdOGDRvk5+en2NhYZWVlKScnR6GhoUpJSdGOHTt8XWKZ1K5dOwUHB8vlcqlSpUpatWqVHA6H/vnPf2rGjBmy2WxasmSJNm/erNdee83X5RrH399f1113naTTX56XL1+uYcOGKSAgwDvdNASYUnb2Hwi73e7dLd+kSROlpKQQXoqJS1IvT1ZWltq0aeMdP5fLpVdeeUVOp1N2u1133323brrpJnXt2tXYf9x85fnnn/d+UVmwYIFef/1172MaYmJiFBMT48vyyqwaNWpo+PDh2rt3rxYsWOCd7na79eabb2r8+PFasGCBunTpwpeWIvrll1/08MMPy+Px6LfffvPeRPG3335TeHi4j6v78wgwPvLHKxS4bfulvfLKKwoJCVFeXp7efPNNSaf/8I4dO1bS6X/oxo4dK4/HoxMnTpzzsEL8z4YNG/T999+rZcuWhc5tKSgo0KFDh7R161b961//0ocffqi7775bL774ImHxPH777Td9++23he6nM2LECNlsNq1YsUJJSUm64447FBwcbOxu+tL0x8MeZ/j7+8tut+uxxx5Tbm6uDyozU3h4uIYOHSqPx6O+fft696babDZdc801Pq7uzyPAlJLff/9dV111lffns29odcMNNxSat2nTppo+fTonTf7Bzp07FRAQoIKCAu9jAyRp7969hX52u93Kzs72RYlGefnll/Xxxx+rT58++uWXXySdPk8rKipKb731lsaPH69ly5Zp/vz5hJcL2Ldvn6ZNm6bDhw9r2bJlkqQnnnhCISEh+v333zVt2jSFhoZy0u5l+O677wq99ng8ev311yWdfhTGLbfc4ouyjOLv76+IiAi53W75+/urfv36vi7JUgSYUrBy5UoNHTpUTz31lCQpLCxMixcvVkBAgHr16qWZM2fK4/HIZrPpxIkT6tatmzZu3KgmTZr4tvAy5t1335UktWzZUhMnTpR0+oneZ35u1KiR92dc2pmAnJmZqffee099+vTRe++9p379+snPz09+fn6qXr26UlJSfFxp2dWkSROlpaXpxx9/1NixY3XllVeqR48estvt+vrrr3XNNdfoxIkTOnTokLp06eLrco0yYsQIBQcHF5oWEBCgkydP6sUXX9SXX37po8rMsW/fPnXr1k0ej0eZmZm6+eabddVVV6ldu3bq3bu38cGaAFMKWrZsqeeff17vvPOOTpw4oYULF3qfAOrn56drrrlGbrfb+weFe8Fc3Nl7A9gzcHm6dOmiX375Rd27d9cvv/yia665Rv7+/rrmmmv0yy+/qEePHt7/5+bmcufTSwgLC9OsWbP02muvyeFwKC4uTvfff7/uuusuHs56mZYvX17oSck2m02PP/64srKyvHsMcXF16tTR4sWLJUmJiYn64osvtH//fv3nP//R3XffbeSl02fjGEUp8Pf3V4cOHZSWlqaAgABNmDBB/fr102+//eZ9+GC/fv300UcfSZL+/ve/q3bt2j6uuuxzuVxyuVy+LsNIzz77rMLDwzV8+HBVq1atUFt4eLhSU1MVHh6uYcOGafDgwT6q0gyHDx9W9+7d9fPPP2vQoEEKCwvT3LlzNWDAAL3wwgtauHChnE6nr8s02pkvKmlpafrggw80YcIEH1dkHrfbrf3790uSHnzwQaWkpCgnJ0f5+fne6aYhwJQim82mwMBALV26VBEREerUqZOcTqdsNptuv/12jRgxQvPmzfN1mWWa0+nUqVOnJJ1+fpS/v7/3fBduKl10zZo1k5+fnxo1aqSAgAC9+OKLyszM1IsvvqjAwEA1atRIgYGBiomJ4cnol/Dyyy+rS5cuiomJkdvt1vDhw3Xo0CHZ7XYlJCRo/vz5uvnmm/Xyyy97b3iHc504cUJLlizRypUrlZOT453u8Xg0dOhQ7dy5U61atdK8efN09OhRH1ZqhjPPMTvjzEnQKSkpSklJ0fvvv6+UlBTZ7Xb17t270JibgkNIpezMPQ5eeOEFXX311Zo/f76k03dJvPbaa9W/f3/l5eXpwQcf9HGlZVN+fr5uvPFGSdKVV16pn376SdLp+xq4XK5znqKM88vNzfV++xowYIBOnjyp2NhYud1uxcfHKz8/n71bRXTm91aSZs2aJT8/Pz3++OOSpA4dOqhDhw7auXOn3n77bd11111avnz5OXu98L87xdaqVavQ+X99+vTR/fffL5fLpYiICHXt2lWTJk3Ss88+68Nqy76zv+xJ0hdffOHDakoGz0IqZRMnTvTeE+LM4aOzrzZat26d/vvf/6pfv36+KtFIeXl5mj17trp37845BxZwu91at26d4uPjfV2KUbKzs3Xs2LELXqJ66NAhVa9evZSrMlNBQYHuueceffzxx4Wm//7779qzZw8XORTB2edWlkcEGABAmeNyufTVV18VenYccLbyG80AAEZwOp1q3759oWkOh4PwgoviHBgAgE8FBATo8OHD50y/4YYb5HA45Ofn571Lr9vtltPp1JYtW3xQKcoSAgwAwOfOd67GlVdeWegeRB6PR8nJyeecF4OKiQADACiT7Hb7OSdEn28aKibOgQEAAMYhwAAAAOMQYAAAPnfixAn17NlTkydP1p49e3xdDgzAOTAAAJ+rVKmS2rdvr+XLl+uNN95Q06ZNVVBQoO+++67QY0LOTGvRogU3razguJEdAMDnWrRoobVr10qStmzZovHjx+u7776T3W5X/fr1vfO53W65XC5NmzZNVapU8VW5KAPYAwMA8Lmzv0s3aNBA7777rmbNmqXRo0erYcOGGjlypA+rQ1nEOTAAAJ/645OTz+jWrZtmz56tzz77TKNHj/ZBZSjLCDAAAJ+y2Wx6/vnnz9tWv359TZgwQf/5z3+0YcOG0i0MZRrnwAAAyryNGzcqNjbW12WgDCHAAAAA43AICQAAGIcAAwAAjEOAAQAAxiHAACgRv/zyi6Kjoy/4uqStWbNGiYmJpfZ+AEoXAQZAqahZs6bWrVtX7OUSExO1Zs2aYi/XrFkzLVq0qNTeD0DpIsAAKBV2u11XXnllqb2fn5+fQkNDS+39AJQuAgwAy3z55Ze6/fbbFR8frwULFhRqu9AhpO+//14dOnRQbGysHnjgAe3du1eS1KdPH0VHR+vXX39Vr169FB0drbffftu7XM+ePZWWlqapU6fqtttu09dff12o3wsdQlq1apU6deqkJk2a6JFHHtHBgweL9H4AyhYCDABLHDlyRAMHDtSjjz6qOXPm6KuvvirSck8//bS6dOmiZcuWqW7dunr99dclSW+88YbWrVuniIgI/fvf/9a6dev00EMPFVp29uzZ+u677/TSSy+pcePGl3yv/fv3q1+/fvrrX/+qpUuXKjQ0VCNGjCjy+wEoO3iYIwBLrFy5UpGRkbr//vslSX/729/Ut2/fSy4XGBiogoIChYWFaeTIkd5n4gQHB0s6fegpODj4vIefTp48qenTpysgIKBINX788cdq3ry57rvvPknSsGHDtHXr1iK/H4Cygz0wACxx+PBhRUREeF9HRUUVablx48ZpzZo1atOmjXr16qUdO3YU+T0feOCBIocXScrIyFBkZKT3dY0aNXTbbbcVeXkAZQcBBoAlqlSposzMTO/rjIyMSy6Tm5srl8ulqVOnavXq1WrWrJmGDRtWaB6bzaYLPfEkKCioWDVGRETo119/9b7es2ePOnfuLLfbXaT3A1B2EGAAWCIhIUG7d+/WRx99pH379umNN9645DIul0t9+vTRokWL9Ntvv8nj8cjlchWap1atWvruu++UmZmpVatW/akaO3bsqB9++EFpaWnKyMjQ5MmTVbVqVdnt//un0Mr3A1ByCDAALFGjRg3985//1Jtvvqnu3buradOml1wmNDRU48aN0+TJk3X77bfryy+/1EsvvVRonqFDh+qrr77SbbfdVqRQdDFRUVGaNGmSpk6dqo4dO+r48eP6xz/+UWLvB6Dk8DRqAABgHPbAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4/w+ugPNACAHMewAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snd.pivot_table(values='price', index='district', columns='school', aggfunc=np.mean).plot(kind='bar')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-06-08T16:12:21.028764Z",
     "end_time": "2024-06-08T16:12:21.225305Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 0, 'Year')"
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 2 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 双轴图\n",
    "# - 按年度汇总GDP，并计算GDP增长率。绘制双轴图。GDP为柱子，GDP增长率为线。\n",
    "gdp = pd.read_csv('../data/gdp_gdpcr.csv', encoding='gbk')\n",
    "gdp.head()\n",
    "# In[45]:\n",
    "\n",
    "x = list(gdp.year)\n",
    "GDP = list(gdp.GDP)\n",
    "GDPCR = list(gdp.GDPCR)\n",
    "fig = plt.figure()\n",
    "\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax1.bar(x, GDP)\n",
    "ax1.set_ylabel('GDP')\n",
    "ax1.set_title(\"GDP of China(2000-2017)\")\n",
    "ax1.set_xlim(2000, 2017)\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(x, GDPCR, 'r')\n",
    "ax2.set_ylabel('Increase Ratio')\n",
    "ax2.set_xlabel('Year')"
   ],
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   "cell_type": "code",
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   "source": [],
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     "start_time": "2024-06-08T16:12:21.557000Z",
     "end_time": "2024-06-08T16:12:21.595244Z"
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